Packet-based voice telecommunications, such as Voice over Internet Protocol, are becoming increasingly important. Such telecommunications offer users greater flexibility at lesser cost. The primary drawback of packet-based voice telecommunications continues to be Quality of Service or QoS. Voice telephony depends on reliable, low latency, real-time delivery of audio data. In VoIP, values for latency, packet loss, and jitter can increase substantially, particularly during periods of heavy network traffic, causing a user to experience a much poorer quality of communication (e.g., audio or video distortion, unacceptable levels of asynchronization between audio and video streams, etc.) than would be experienced if the call were made by a traditional circuit-switched telephony network.
Network measurement systems are normally employed to monitor the causes of QoS problems, such as a failure of a link or system component and traffic congestion (e.g., blackouts and brownouts), and to ensure compliance by service providers with Service Level Agreements. For example, monitors collect Real-Time Control Protocol or RTCP packets and test agents generate and send test packets to collect network metrics that can be used for a variety of purposes including call admission control. FIG. 1 shows a typical hierarchical network measurement system. The wireline and/or wireless network backbone comprises first and second Local Area Networks or LANs 104a,b connected by a Wide Area Network or WAN 108.
The network backbone is divided into zones, based on suitable criteria, such as physical or logical location. In a first zone 120a, the first LAN 104a interconnects a first server 112a and first, second, and third test agents 116a-c. In a second zone 120b, the second LAN 104b interconnects a second server 112b and first, second, third, fourth and fifth test agents 116d-h. The agents measure one or more parameters indicative of communication path quality, such as round trip time, jitter buffer delay, jitter, packet loss burst size, a number of our-of-order packets, an out-of-order distance, Reservation Protocol status, call state, sender channel state, IP Differential Service Code Point, available bandwidth, router buffer size, latency, packet loss, router bandwidth utilization, router processor utilization, and/or bit error rate.
The system 100 gathers both zone-to-zone measurements and test agent-to-test agent measurements within a zone. Zone-to-zone measurements between two zones, such as the first and second zones 120a,b (and over the WAN 108), are obtained by testing between any test agent in the first zone 120a and any agent in the second test zone 120b. If only zone-to-zone measurements were of interest, a pair of test agents in the first and second zones could be randomly selected, and a measurement conducted between them. The random selection and measurement performance would be repeated at selected time intervals to provide a steady rate of measurements between the first and second zones.
This approach can result in potentially very large inter-measurement periods between agent test pairs. For example, assuming that the first and second zones each had ten agents and that a measurement were to be conducted between the first and second zones at every period T, the average period of measurements between a given test agent in the first zone and a test agent in the second zone is 100T, that is, there is a 1% probability that this period is ten times as large, i.e., 1,000T. Given that the monitoring system uses these test measurement results to arrive to conclusions about the connectivity between the test agents, it is highly desirable to maintain the measurement period between members of a given test agent pair as small and as regular as possible (ideally less than 200T).
To realize a relatively small and regular measurement period between the members of a test agent pair by scheduling between the test agents in the first and second zones in a round robin fashion. However, the round robin approach can lead to two problems. First, the randomness in the sequence of test agent pairs being tested can be lost. This can adversely affect the measurement results. Loss of randomness in the measurement periods and sequences can cause synchronization effects to occur. Second, “shotgun” effects can take place. Such effects occur when a selected test agent is exercised too intensely. For example, a simple double for loop across the two sets of test agents corresponding to the two zones would result in having each test agent in the first zone send measurements, in sequence, to all test agents in the second zone. This can over-load the test agent. Test agents may be embedded in a critical device (e.g., phone), and overloading the test agent can result in potentially disastrous problems affecting the critical device.